Research Areas

The research at the Bioprocess Development Lab is focused on the optimization and intensification of several bioprocesses of industrial interest. Research efforts are currently focused on increasing the understanding of the dynamic behaviour of photobiological systems in the presence of light and in the dark. Applied work is also conducted for developing new sensors and tools for measuring and controlling cells behaviour inside the bioreactor.

If you are currently developing a microalgal based process and are strugling with low cell densities and meager productivities, we can help you to get the most out of your strain and significantly improve process economics. Please contact us

If you are a prospective student interested on biofuels, renewable energy, carbon capture and sequestration, or green chemistry, and you have a bachelor degree in Chemical or Biochemical Engineering from an acredited university, please check current opportunities open in our group.

 

Microalgae as a biofuels feedstock

Microalgae are of great interest as a source of biofuels (green diesel, biodiesel, hydrogen, and ethanol), nutraceuticals, and other fine and bulk chemicals. Microalgae are photosynthetic unicellular organisms that use light and CO2 to power their metabolism. Certain microalgae strains are also capable of growing in the dark feeding on organic carbon sources. Whether they are growing phototrophically (with light) or heterotrophycally (in the dark), microalgae are highly efficient organisms capable of accumulating large amounts of lipids or starch, as well as other high-value chemicals. The accumulated lipids (or starch) can later be converted into diesel (or ethanol). Other algal strains can be manipulated to direct their metabolism for the production of hydrogen or the direct production of ethanol (without intermediate starch accumulation).

Despite the great potential of microalgae, current commercial applications are limited to very-high value, low-volume, products. This is due mainly to the very low cell densities that characterize microalgal culture systems (normally less than 1 g/L, dry weight) and high processing costs associated with the handling of large amounts of liquids and harvesting from very diluted streams.

In our group, we are developing bioreactors configurations and novel culturing strategies to boost both cell density and productivity of microalgal cultures. Biomass productivity targets are 40 g/Ld in heterotrophic systems (already achieved), and 5 g/Ld for phototrophic systems.

 

Development of multivariate sensors for bioprocess monitoring

In a bioreactor, an ideal sensor should provide information regarding the activity, physiological state, or other characteristic of the cells that directly affect the process outcome. Image-based and hyper-spectral sensors have the potential to provide such information. Other measurement techniques may be based on amperometric, potentiometric, and conductometric principles. Currently we are working on developing a flow-through image-based sensor to characterize the cell status inside a bioreactor.

Chemical characterization of the culture medium is also very important as it allows to determine if inhibitory metabolites are being accumulated in the medium or if a required nutrient is being exhausted. Multivariate spectroscopy-based sensors are also being developed for quantifying the biochemical composition of microalgal cultures.

 

Population dynamics of microalgal cultures

Batch to batch variability is a defining characteristic of biological reactions that continues to puzzle biochemical engineers: cultures performed under seemingly identical conditions may produce very different results. Currently, most engineering models of bioreactors fail to satisfactorily describe the dynamics of cellular growth, particularly in eukaryotic systems, where cells undergo a growth cycle and multimodality in the population distribution may occur.

Models that describe the variations in a cell and across a cell population can provide a more realistic description of a bioreaction system. Accounting for multimodality in the models may also help to explain the variability observed in cell cultures, and allow the construction of control tools to reduce or eliminate such variations.